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<p>We propose a novel two-layer framework to analyze online browsing patterns and their relationship with purchase behavior in e-commerce. By applying sequence analysis—a method adapted from bioinformatics—to comprehensive clickstream data, we capture the temporal dynamics of consumers’ shopping goal concreteness and identify how marketing stimuli reshape navigation paths. Our Layer 1 analysis categorizes consumers into eight distinct browsing patterns differentiated by shopping goal concreteness and path towards goal attainment. Layer 2 examines how marketing stimuli adjust these patterns, uncovering eight additional browsing behaviors. Post-framework analyses reveal that personalized recommendations drive purchases primarily when consumers have general shopping goals in early exploration stages, whereas price promotions are most effective for those with concrete goals. These effects also vary by product type. Additionally, our pattern-based framework serves as a complementary layer that enhances existing clickstream-based purchase prediction models by enabling pattern-specific hyperparameter optimization and reducing noise from irrelevant data points. This research provides both theoretical insights into online shopping behavior and practical guidance for optimizing marketing strategies.</p>

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Understanding consumers’ online browsing patterns and influence of marketing stimuli: A two-layer sequence analysis approach

  • 期刊论文

  • 发表日期：

    2025年6月7日

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  • Yi Ding,
  • Haifeng Xu,
  • Chee Wei Phang,
  • Bernard C. Y. Tan

摘要

We propose a novel two-layer framework to analyze online browsing patterns and their relationship with purchase behavior in e-commerce. By applying sequence analysis—a method adapted from bioinformatics—to comprehensive clickstream data, we capture the temporal dynamics of consumers’ shopping goal concreteness and identify how marketing stimuli reshape navigation paths. Our Layer 1 analysis categorizes consumers into eight distinct browsing patterns differentiated by shopping goal concreteness and path towards goal attainment. Layer 2 examines how marketing stimuli adjust these patterns, uncovering eight additional browsing behaviors. Post-framework analyses reveal that personalized recommendations drive purchases primarily when consumers have general shopping goals in early exploration stages, whereas price promotions are most effective for those with concrete goals. These effects also vary by product type. Additionally, our pattern-based framework serves as a complementary layer that enhances existing clickstream-based purchase prediction models by enabling pattern-specific hyperparameter optimization and reducing noise from irrelevant data points. This research provides both theoretical insights into online shopping behavior and practical guidance for optimizing marketing strategies.